Category: Amazon Redshift

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. In this post, we discuss how to successfully conduct a proof of concept in Amazon Redshift by going through the main stages of the process, available tools that accelerate implementation, and common use cases.

Amazon Relational Database Service (Amazon RDS) for MySQL zero-ETL integration with Amazon Redshift was announced in preview at AWS re:Invent 2023 for Amazon RDS for MySQL version 8.0.28 or higher. In this post, we provide step-by-step guidance on how to get started with near real-time operational analytics using this feature. This post is a continuation […]

AWS is now announcing data filtering on zero-ETL integrations, enabling you to bring in selective data from the database instance on zero-ETL integrations between Amazon Aurora MySQL and Amazon Redshift. This feature allows you to select individual databases and tables to be replicated to your Redshift data warehouse for analytics use cases. In this post, we provide an overview of use cases where you can use this feature, and provide step-by-step guidance on how to get started with near real time operational analytics using this feature.

It always pays to know more about your customers, and AWS Data Exchange makes it straightforward to use publicly available census data to enrich your customer dataset. The United States Census Bureau conducts the US census every 10 years and gathers household survey data. This data is anonymized, aggregated, and made available for public use. […]

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, straightforward, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the most widely used cloud data warehouse. You can run […]

This post is cowritten with Amy Tseng, Jack Lin and Regis Chow from BMO. BMO is the 8th largest bank in North America by assets. It provides personal and commercial banking, global markets, and investment banking services to 13 million customers. As they continue to implement their Digital First strategy for speed, scale and the […]

This post is co-written with Toney Thomas and Ben Vengerovsky from Bluestone. In the ever-evolving world of finance and lending, the need for real-time, reliable, and centralized data has become paramount. Bluestone, a leading financial institution, embarked on a transformative journey to modernize its data infrastructure and transition to a data-driven organization. In this post, […]

You can ingest and integrate data from multiple Internet of Things (IoT) sensors to get insights. However, you may have to integrate data from multiple IoT sensor devices to derive analytics like equipment health information from all the sensors based on common data elements. Each of these sensor devices could be transmitting data with unique […]

Now, at Amazon Redshift, we are announcing the general availability of multi-data warehouse writes through data sharing. This new capability allows you to achieve better performance for extract, transform, and load (ETL) workloads by using different warehouses of different types and sizes based on your workload needs.

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3). Furthermore, they are adopting security models that require access to the data lake […]